Space weatherSpace weather

Henrik Lundstedt

Swedish Institute of Space Physics, Lund, Sweden

www.lund.irf.se

OutlineOutline

• Solar activity - the driver of space weather

• Forecast methods

• Applications

• Implementations for users

• Forecast centers (ISES/RWCs)

Space weather was mentioned for the first time in Swedish media 1991

The US National Space Weather Program 1995: Space weather refers to conditions on the sun, and in the solar wind, magnetosphere, ionosphere and thermosphere that can influence the performance and reliability of space-borne and ground-based technological systems and Endanger human life or health.

ESA Space Weather Programme started in April 1999.

We started early in LundWe started early in Lund

HD 1981 (cycle 21)

SDS 1991 (cycle 22)SDS 1991 (cycle 22) Arbetet 1981 (cycle 21)

Why are space weather programs (ILWS/ESASWP) important?

Why are space weather programs (ILWS/ESASWP) important?

• They raise fundamental questions within space physics (about e.g. solar activity within solar physics)

• They require a new scientific approach: an interdisciplinary approach (Knowledge from many disciplines

must be used: solar physics, interplanetary, magnetospheric, ionospheric, atmospheric physics, physics about dynamic nonlinear systems, IHS and so on)

• They show how fundamental forecasting is within science and again that a new approach is needed (Knowled-based neural models)

• Forecasts of real-world events are also the real test of a model

Solar activitySolar activity

• Solar activity is the driver of space weather• Better understanding and improved

forecasts of solar activity are therefore a prime goal within space weather programs and a real challenge

• Let me therefore now discuss new observation facilities, some new research results and attempts to forecast solar activity

Solar observations with the new Swedish solar telescope on La Palma

Solar observations with the new Swedish solar telescope on La Palma

2002

1980-2002

1951-1980

Anacapri, Capri, Italy

Solar OrbiterSolar Orbiter

The orbit at heliocentric distanceof 45 Rs and out-of ecliptic atheliographic latitudes of up to38 degrees gives a 0.”05 resolutionand a possibility to study thepolar field that determines the11 years solar cycle.

Launch 2009.

SDOSDO

SOHO has given us a totally new picture of the Sun- always activeSOHO has given us a totally new picture of the Sun- always active

• Solar Heliospheric Observatory was launched on December 2, 1995

• SOHO carries three instruments observing the solar interior, six the solar corona and three the solar wind

QuickTime och enCinepak-dekomprimerare

krävs för att kunna se bilden.

The oscillations reveal solar interior

The oscillations reveal solar interior

MDI/SOHO reveals the interiorand explains surface activity

MDI/SOHO reveals the interiorand explains surface activity

MDI shows how magnetic elements form sunspots

MDI shows how the dynamo changes (1.3y)

Sunspots are footpointsof emerging magnetic flux tubes

Change of the nature of solar activity 1850 - 2000

Change of the nature of solar activity 1850 - 2000

High frequency content (2-4 days period) decreases with time, while the low frequency content (20-128 days) increases with time during the 150

years period. Daily sunspot numbers were used.

Wavelet power spectra reveals solar activity periodicities

Wavelet power spectra reveals solar activity periodicities

WSO solar mean field May 16, 1975 - March 13, 2001

Wavelet power spectra shows 13,5, days 27 days, 154 days, 1.3 years periodicities

Sunspot solar cycles Sunspot solar cycles

Schwabe found the 11- year sunspot solar cycle. R = k(10g + f).Gleissberg found the 80-90 years cycle.Maunder-Spörer 207 years cycle,Houtermans cycle 2272 years and Sharma 100 000 years cycle.

The two peaks of solar activity, 1.3 years separated!

Solar activity and North Atlantic Oscillation Index

Solar activity and North Atlantic Oscillation Index

Solar Polar FieldSolar Polar Field

The solar magnetic field further expand and CMEs occur

The solar magnetic field further expand and CMEs occur

Proton events give positiveNAO within days!

Fast halo coronal mass ejection

Daily solar activity and NAODaily solar activity and NAO

March 16 - April 10, 1999 (1 min time resolution)

Solar mean field and wavelet power spectra

Solar mean field and wavelet power spectra

Wavelet power spectra of MDI magnetic mean field

Wavelet power spectra of MDI magnetic mean field

Upper panel shows for 53 CME events.Lower panel shows for times without CMEs.

Forecast MethodsForecast Methods

• First principles (MHD models) (MHD models of the whole Sun-Earth Connection

are good at explaining and good for education, but not so good at forecasting.)

• Linear and nonlinear filters (MA, ARMA, NARMA)

MA filter applied as linear filter of AL.The impulse response Dst is predicted with an ARMA filter. function H of the magnetospheric system is convolved with

a sequence of solar wind inputs (Problems: Linearity, nonstationary systems, high dimensions)

• Knowledge-Based Neural Models (KBNM) i.e. Knowledge (Diff eqs of physics, dynamical system analysis, filters, information

theory, expert, fuzzy rules) based neural networks

Neural network prediction of Dst, 1990

Neural network prediction of Dst, 1990

Download Lund Dst model in Java and Matlab (www.lund.irf.se/dst/models)

Download Lund Dst model in Java and Matlab (www.lund.irf.se/dst/models)

Workshops arranged by usWorkshops arranged by us

Workshops on ”Artificial Intelligence Applications in Solar-Terrestrial Physics” were held in Lund 1993 and 1997.

ApplicationsApplicationsInput parameters Output KBNM

methodReference

Daily sunspot number Daily sunspot number SOM and MLP

Liszka 93;97

Monthly sunspot number Date of solar cycle max and amplitude

MLP and Elman

Macpherson et al., 95, Conway et al, 98

Monthly sunspot number and aa

Date of solar cycle max and amplitude

Elman Ashmall and Moore, 98

Yearly sunspot number Date of solar cycle max and amplitude

MLP Calvo et al., 95

McIntosh sunspot class & MW magn complex.

X class solar flare MLP expert system

Bradshaw et al., 89

Flare location, duration

X-ray and radio flux

Proton events MLP Xue et al., 97

X-ray flux Proton events Neuro- fuzzy system

Gabriel et al., 00

Photospheric magnetic field expansion factor

Solar wind velocity 1-3 days ahead

RBF & PF MHD

Wintoft and Lundstedt 97;99

ApplicationsApplications

Input parameters Output KBNM method Reference

Solar wind n, V, Bz

Relativistic electrons in Earth magnetosphere hour ahead

MLP Wintoft and Lundstedt, 00

Solar wind n,V, Bz, Dst

Relativistic electrons hour ahead

MLP, MHD, MSFM

Freeman et al., 93

Kp Relativistic electrons day ahead

MLP Stringer and McPherron, 93

Solar wind V from photospheric B

Daily geomagnetic Ap index

MLP Detman et al., 00

Ap index Ap index MLP Thompson, 93

Solar wind n, V, Bz

Kp index 3 hours ahead MLP Boberg et al., 00

Solar wind n, V, B,Bz

Dst 1-8 hours ahead MLP, Elman Lundstedt, 91; Wu and Lundstedt, 97

Solar wind n, V, B,Bz

AE 1 hour ahead Elman Gleisner and Lundstedt, 00

ApplicationsApplications

Input parametrs Output KBNM method References

Solar wind V2Bs, (nV2)1/2, LT, local geomag xe, Yw

Local geomagnetic field X,Y

MLP and RBF Gleisner and Lundstedt 00

Solar wind n,V, Bz None, weak or strong aurora

MLP Lundstedt et al., 00

foF2 foF2 1 hour ahead MLP Wintoft and Lundstedt, 99

AE, local time, seasonal information

foF2 1-24 hours ahead

MLP Wintoft and Cander, 00

foF2, Ap, F10.7 cm 24 hours ahead MLP Wintoft and Cander, 99

Kp Satellite anomalies MLP Wintoft and Lundstedt 00

Solar wind n, V, Bz GIC Elman, MLP Kronfeldt et al., 01

Real-time forecasts and warnings based on KBN Real-time forecasts and warnings based on KBN

Solar wind observations with ACE make accurate forecasts 1-3 hours ahead possible.

Solar observations with SOHO make warnings 1-3days ahead possible.

Solar input data

The NAO response on increased solar wind E, one month later! That makes forecasts one month ahead possible.

North Atlantic Oscillation and solar wind activity

North Atlantic Oscillation and solar wind activity

11 års, 1.3 variations are seen both insolar wind and NAO.

ESA/Lund Space Weather Forecast Service

ESA/Lund Space Weather Forecast Service

Near and farside solar activity from MDI/SOHO observationsNear and farside solar activity from MDI/SOHO observations

Latest information on arrival of halo CME at L1

Latest information on arrival of halo CME at L1

Latest info on forecasts of satellite anomalies (SAAPS)Latest info on forecasts of

satellite anomalies (SAAPS)

Latest information on forecasts of Kp, Dst, AE and GIC

Latest information on forecasts of Kp, Dst, AE and GIC

Forecast Centers (ISES/RWC)

Forecast Centers (ISES/RWC)

David Boteler, Director (Canada)Henrik Lundstedt, Deputy Director

Today’s space weatherToday’s space weather

Forecasts of aurora as SMS, voice messages or WAP service

Forecasts of aurora as SMS, voice messages or WAP service

Knowledge-Based Neural Models

Knowledge-Based Neural Models

The basis of using neural networks as mathematical models is ”mapping”. Given a dynamic system, a neural network can model it on the basis of a set of examples encoding the input/output behavior of the system. It can learn the mathematical function underlying the system operation (i.e. generalize not just fita curve), if the network is designed (architechure, weights) and trained properly(learning algorithm).

Both architechure and weights can be determined from differential equations which describe the causal relations between the physical variables (solution ofdiff eq is approximized by a RBF). The network (KBN) is then trained with observations.

The architechure (number of input and hidden nodes) can also be determined from dynamic system analysis (reconstruction of state space from time series gives dimension).

Neural networks can discover laws from regularities in data (Newton’s law e.g.).If one construct a hierachy of neural networks where networks at each level can learn knowledge at some level of abstraction, even more advanced laws can bedicovered.

Cosmic ray variation at time ofsolar wind IR and VAI (storminess)

Solar-weather relations 1981Solar-weather relations 1981

Medelvärdesbildade longitudinella fotosfärsmagnetfältet

1975-2000